Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_plot

beta_std plot

beta_std_plot

Metadata

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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30720_irnt/ukb-d-30720_irnt.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30720_irnt/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 14:54:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30720_irnt/ukb-d-30720_irnt.vcf.gz ...
Read summary statistics for 13586046 SNPs.
Dropped 12711 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2548 (0.0755)
Lambda GC: 1.8018
Mean Chi^2: 3.1695
Intercept: 1.1687 (0.0175)
Ratio: 0.0778 (0.0081)
Analysis finished at Mon Nov 25 14:56:38 2019
Total time elapsed: 2.0m:17.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.4754,
    "mean_EFFECT": 0,
    "n": 344264,
    "n_snps": 13586046,
    "n_clumped_hits": 316,
    "n_p_sig": 70687,
    "n_mono": 0,
    "n_ns": 1251777,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 569176,
    "n_est": 345596.9493,
    "ratio_se_n": 1.0019,
    "mean_diff": 6.1795e-06,
    "ratio_diff": 4.1029,
    "sd_y_est1": 0.9064,
    "sd_y_est2": 0.9081,
    "r2_sum1": 0.0679,
    "r2_sum2": 0.0827,
    "r2_sum3": 0.0823,
    "r2_sum4": 0.082,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.2548,
    "ldsc_observed_scale_h2_se": 0.0755,
    "ldsc_intercept_beta": 1.1687,
    "ldsc_intercept_se": 0.0175,
    "ldsc_lambda_gc": 1.8018,
    "ldsc_mean_chisq": 3.1695,
    "ldsc_ratio": 0.0778
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13573999 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57079 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051233e+00 6.184968e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 <U+2587><U+2585><U+2585><U+2582><U+2582>
numeric POS 0 1.0000000 NA NA NA NA NA 7.902571e+07 5.591524e+07 3.02000e+02 3.293108e+07 7.013935e+07 1.148601e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.620000e-05 1.391560e-02 -4.33170e-01 -4.335200e-03 3.540000e-05 4.404400e-03 3.744200e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA 9.179000e-03 8.854200e-03 1.79590e-03 2.613400e-03 4.815800e-03 1.319100e-02 4.472400e-02 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.356050e-01 3.063353e-01 0.00000e+00 1.533900e-01 4.126302e-01 7.007805e-01 1.000000e+00 <U+2587><U+2585><U+2585><U+2585><U+2585>
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.356045e-01 3.063356e-01 0.00000e+00 1.533926e-01 4.126255e-01 7.007747e-01 9.999999e-01 <U+2587><U+2585><U+2585><U+2585><U+2585>
numeric AF 0 1.0000000 NA NA NA NA NA 1.908090e-01 2.544041e-01 1.00000e-03 7.431400e-03 6.003900e-02 2.953200e-01 9.990000e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 569176 0.9581058 NA NA NA NA NA 1.963385e-01 2.471023e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric N 0 1.0000000 NA NA NA NA NA 3.442640e+05 0.000000e+00 3.44264e+05 3.442640e+05 3.442640e+05 3.442640e+05 3.442640e+05 <U+2581><U+2581><U+2587><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0025381 0.0038263 0.5071203 0.5071192 0.1105100 0.1894970 344264
1 693731 rs12238997 A G -0.0000961 0.0036138 0.9787800 0.9787757 0.1157900 0.1417730 344264
1 707522 rs371890604 G C 0.0006558 0.0040650 0.8718300 0.8718289 0.0972240 0.1293930 344264
1 717587 rs144155419 G A -0.0092357 0.0097027 0.3411701 0.3411634 0.0156620 0.0045926 344264
1 723329 rs189787166 A T -0.0137340 0.0285680 0.6306799 0.6306958 0.0017377 0.0003994 344264
1 730087 rs148120343 T C -0.0000858 0.0050367 0.9864200 0.9864157 0.0564140 0.0127796 344264
1 731718 rs142557973 T C 0.0004007 0.0034275 0.9069401 0.9069358 0.1216800 0.1543530 344264
1 732032 rs61770163 A C 0.0009104 0.0036575 0.8034399 0.8034385 0.1210800 0.1555510 344264
1 734349 rs141242758 T C 0.0003398 0.0034293 0.9210600 0.9210643 0.1209100 0.1525560 344264
1 740284 rs61770167 C T 0.0030789 0.0157290 0.8448000 0.8448084 0.0057570 0.0023962 344264
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0010253 0.0039605 0.7957299 0.7957267 0.056184 0.0309934 344264
23 154923374 rs111332691 T A 0.0029030 0.0043472 0.5042698 0.5042701 0.044880 0.0116556 344264
23 154925045 rs509981 C T 0.0102430 0.0020941 0.0000010 0.0000010 0.245660 0.3634440 344264
23 154925895 rs538470 C T 0.0102680 0.0021421 0.0000016 0.0000016 0.242000 0.3634440 344264
23 154927581 rs644138 G A 0.0088043 0.0019694 0.0000078 0.0000078 0.302230 0.4635760 344264
23 154929412 rs557132 C T 0.0102130 0.0020947 0.0000011 0.0000011 0.245520 0.3568210 344264
23 154929637 rs35185538 CT C 0.0088725 0.0021862 0.0000494 0.0000494 0.229770 0.3011920 344264
23 154929952 rs4012982 CAA C 0.0102170 0.0022030 0.0000035 0.0000035 0.239490 0.3165560 344264
23 154930230 rs781880 A G 0.0104000 0.0020944 0.0000007 0.0000007 0.245920 0.3618540 344264
23 154930487 rs781879 T A 0.0189920 0.0071796 0.0081624 0.0081625 0.019561 0.1263580 344264

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11051  ES:SE:LP:AF:SS:ID   -0.0025381:0.0038263:0.294889:0.11051:344264:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11579  ES:SE:LP:AF:SS:ID   -9.6141e-05:0.0036138:0.00931491:0.11579:344264:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097224 ES:SE:LP:AF:SS:ID   0.00065583:0.004065:0.0595682:0.097224:344264:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -0.0092357:0.0097027:0.467029:0.015662:344264:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017377    ES:SE:LP:AF:SS:ID   -0.013734:0.028568:0.200191:0.0017377:344264:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056414 ES:SE:LP:AF:SS:ID   -8.5756e-05:0.0050367:0.00593813:0.056414:344264:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12168  ES:SE:LP:AF:SS:ID   0.00040069:0.0034275:0.0424214:0.12168:344264:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12108  ES:SE:LP:AF:SS:ID   0.00091035:0.0036575:0.0950466:0.12108:344264:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12091  ES:SE:LP:AF:SS:ID   0.00033982:0.0034293:0.0357121:0.12091:344264:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.005757 ES:SE:LP:AF:SS:ID   0.0030789:0.015729:0.0732461:0.005757:344264:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018608    ES:SE:LP:AF:SS:ID   -0.00038596:0.029826:0.00450521:0.0018608:344264:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86983  ES:SE:LP:AF:SS:ID   -0.00094852:0.0033811:0.108424:0.86983:344264:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015195    ES:SE:LP:AF:SS:ID   -0.016389:0.030732:0.226331:0.0015195:344264:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12285  ES:SE:LP:AF:SS:ID   0.0012133:0.0033483:0.144438:0.12285:344264:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14267  ES:SE:LP:AF:SS:ID   0.0015235:0.0033092:0.190285:0.14267:344264:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12297  ES:SE:LP:AF:SS:ID   0.0012291:0.0033436:0.146801:0.12297:344264:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87098  ES:SE:LP:AF:SS:ID   -0.00066297:0.0032587:0.0763468:0.87098:344264:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87555  ES:SE:LP:AF:SS:ID   -0.0012063:0.0033124:0.145251:0.87555:344264:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12855  ES:SE:LP:AF:SS:ID   0.00077651:0.0032667:0.0903851:0.12855:344264:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036324 ES:SE:LP:AF:SS:ID   0.0021602:0.0059301:0.145299:0.036324:344264:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87057  ES:SE:LP:AF:SS:ID   -0.0005846:0.0032553:0.066776:0.87057:344264:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87068  ES:SE:LP:AF:SS:ID   -0.0006241:0.0032568:0.0715888:0.87068:344264:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87057  ES:SE:LP:AF:SS:ID   -0.00056683:0.0032552:0.0646137:0.87057:344264:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050487    ES:SE:LP:AF:SS:ID   0.00037153:0.016695:0.00777796:0.0050487:344264:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050157    ES:SE:LP:AF:SS:ID   -5.7063e-05:0.01674:0.00118289:0.0050157:344264:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055433    ES:SE:LP:AF:SS:ID   0.003382:0.01625:0.0782459:0.0055433:344264:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   -0.00070958:0.0032495:0.0824157:0.87066:344264:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.1259   ES:SE:LP:AF:SS:ID   0.0011265:0.0033155:0.13428:0.1259:344264:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87023  ES:SE:LP:AF:SS:ID   -0.00045021:0.0032418:0.0508296:0.87023:344264:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   -0.00093273:0.0032388:0.111618:0.8695:344264:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   -0.00051655:0.0032445:0.0587321:0.87037:344264:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   -0.00051381:0.0032447:0.0583991:0.87038:344264:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87039  ES:SE:LP:AF:SS:ID   -0.00052452:0.0032448:0.0596927:0.87039:344264:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87083  ES:SE:LP:AF:SS:ID   -0.0005789:0.003253:0.0661282:0.87083:344264:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09877  ES:SE:LP:AF:SS:ID   0.00073002:0.0037809:0.072173:0.09877:344264:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006431 ES:SE:LP:AF:SS:ID   0.00062602:0.014678:0.0150319:0.006431:344264:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87472  ES:SE:LP:AF:SS:ID   -0.00064268:0.0033014:0.0728093:0.87472:344264:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86413  ES:SE:LP:AF:SS:ID   -0.0010446:0.0032381:0.126674:0.86413:344264:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   -0.00067006:0.003269:0.0769685:0.86951:344264:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86645  ES:SE:LP:AF:SS:ID   -0.0006346:0.0032696:0.0725732:0.86645:344264:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098724 ES:SE:LP:AF:SS:ID   -0.00058379:0.003914:0.0548122:0.098724:344264:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87164  ES:SE:LP:AF:SS:ID   -0.0010882:0.003307:0.129526:0.87164:344264:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87164  ES:SE:LP:AF:SS:ID   -0.0010884:0.003307:0.129555:0.87164:344264:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87164  ES:SE:LP:AF:SS:ID   -0.0010776:0.0033071:0.128106:0.87164:344264:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87201  ES:SE:LP:AF:SS:ID   -0.0011077:0.0033089:0.132055:0.87201:344264:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12549  ES:SE:LP:AF:SS:ID   0.0008784:0.0033112:0.101933:0.12549:344264:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10538  ES:SE:LP:AF:SS:ID   0.00079418:0.0036056:0.0831988:0.10538:344264:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85548  ES:SE:LP:AF:SS:ID   -0.00057908:0.0032367:0.0665077:0.85548:344264:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016566    ES:SE:LP:AF:SS:ID   -0.015634:0.02864:0.232733:0.0016566:344264:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83826  ES:SE:LP:AF:SS:ID   -0.0042406:0.0031866:0.736909:0.83826:344264:rs376645387